Publication Type
Working Paper
Version
publishedVersion
Publication Date
8-2020
Abstract
Using an unsupervised machine learning approach to analyze 12.8 million tweets posted by S&P 1500 firms from 2012 to 2016, we find that firms tweet more financial information around significantly negative or positive earnings announcements or accounting filings. Specifically, we observe a symmetric U-shaped relation between the number of financial tweets and the materiality of accounting information events. This relation is consistent with the theoretical prediction in Hummel et al. (2018) which assumes that managers are sensitive to their firm’s fundamental value. We document that this relation also holds for hyperlink usage in tweets about financial information around important events, and that the relation is more pronounced for non-loss firms. Furthermore, our intraday analyses indicate that firms release financial information on Twitter primarily after (before) earnings announcements (10-K or 10-Q filings), suggesting that Twitter plays different roles for firms around separate accounting information events.
Keywords
Social Media, Discretionary Dissemination, Disclosures, Twitter, Feedback
Discipline
Accounting | Corporate Finance | Social Media
Research Areas
Corporate Reporting and Disclosure
First Page
1
Last Page
60
Identifier
10.2139/ssrn.3105847
Publisher
Singapore Management University School of Accountancy Research Paper No. 2022-148
City or Country
Singapore
Citation
CROWLEY, Richard M.; HUANG, Wenli; and LU, Hai.
Discretionary dissemination on Twitter. (2020). 1-60.
Available at: https://ink.library.smu.edu.sg/soa_research/1776
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.2139/ssrn.3105847
Included in
Accounting Commons, Corporate Finance Commons, Social Media Commons
Comments
Published in Contemporary Accounting Research (2024). DOI: 10.1111/1911-3846.12986